The performance and the uncertainty of receptor models (RMs) were assessed in intercomparison exercises employing real-world and synthetic input datasets. To that end, the results obtained by different practitioners using ten different RMs were compared with a reference. In order to explain the differences in the performances and uncertainties of the different approaches, the apportioned mass, the number of sources, the chemical profiles, the contribution-to-species and the time trends of the sources were all evaluated using the methodology described in Belis et al. (2015). In this study, 87% of the 344 source contribution estimates (SCEs) reported by participants in 47 different source apportionment model results met the 50% standard uncertainty quality objective established for the performance test. In addition, 68% of the SCE uncertainties reported in the results were coherent with the analytical uncertainties in the input data. The most used models, EPA-PMF v.3, PMF2 and EPA-CMB 8.2, presented quite satisfactory performances in the estimation of SCEs while unconstrained models, that do not account for the uncertainty in the input data (e.g. APCS and FA-MLRA), showed below average performance. Sources with well-defined chemical profiles and seasonal time trends, that make appreciable contributions (>10%), were those better quantified by the models while those with contributions to the PM mass close to 1% represented a challenge. The results of the assessment indicate that RMs are capable of estimating the contribution of the major pollution source categories over a given time window with a level of accuracy that is in line with the needs of air quality management.
A new methodology to assess the performance and uncertainty of source apportionment models II : the results of two European intercomparison exercises / C.A. Belis, F. Karagulian, F. Amato, M. Almeida, P. Artaxo, D.C.S. Beddows, V. Bernardoni, M.C. Bove, S. Carbone, D. Cesari, D. Contini, E. Cuccia, E. Diapouli, K. Eleftheriadis, O. Favez, I. El Haddad, R.M. Harrison, S. Hellebust, J. Hovorka, E. Jang, H. Jorquera, T. Kammermeier, M. Karl, F. Lucarelli, D. Mooibroek, S. Nava, J.K. Nøjgaard, P. Paatero, M. Pandolfi, M.G. Perrone, J.E. Petit, A. Pietrodangelo, P. Pokorná, P. Prati, A.S.H. Prevot, U. Quass, X. Querol, D. Saraga, J. Sciare, A. Sfetsos, G. Valli, R. Vecchi, M. Vestenius, E. Yubero, P.K. Hopke. - In: ATMOSPHERIC ENVIRONMENT. - ISSN 1352-2310. - 123(2015), pp. 240-250. [10.1016/j.atmosenv.2015.10.068]
A new methodology to assess the performance and uncertainty of source apportionment models II : the results of two European intercomparison exercises
V. Bernardoni;G. Valli;R. Vecchi;
2015
Abstract
The performance and the uncertainty of receptor models (RMs) were assessed in intercomparison exercises employing real-world and synthetic input datasets. To that end, the results obtained by different practitioners using ten different RMs were compared with a reference. In order to explain the differences in the performances and uncertainties of the different approaches, the apportioned mass, the number of sources, the chemical profiles, the contribution-to-species and the time trends of the sources were all evaluated using the methodology described in Belis et al. (2015). In this study, 87% of the 344 source contribution estimates (SCEs) reported by participants in 47 different source apportionment model results met the 50% standard uncertainty quality objective established for the performance test. In addition, 68% of the SCE uncertainties reported in the results were coherent with the analytical uncertainties in the input data. The most used models, EPA-PMF v.3, PMF2 and EPA-CMB 8.2, presented quite satisfactory performances in the estimation of SCEs while unconstrained models, that do not account for the uncertainty in the input data (e.g. APCS and FA-MLRA), showed below average performance. Sources with well-defined chemical profiles and seasonal time trends, that make appreciable contributions (>10%), were those better quantified by the models while those with contributions to the PM mass close to 1% represented a challenge. The results of the assessment indicate that RMs are capable of estimating the contribution of the major pollution source categories over a given time window with a level of accuracy that is in line with the needs of air quality management.File | Dimensione | Formato | |
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